Operations Research, Systems Engineering and Industrial Engineering Commons^™

Quantifying Lock Criticality For Inland Waterway Navigation Using An Agent-Based Simulation, Ashwin Narayan

Industrial Engineering Undergraduate Honors Theses

Inland waterway travel has tremendous potential to improve multimodal transportation in the United States due to its environment-friendly and safe nature. Waterway travel has proven to be much cheaper per ton-mile and more fuel efficient than trucks. Millions of dollars have recently been invested in inland waterway networks to facilitate travel. The waterway infrastructure must be resilient to enable efficient waterway travel and prevent unnecessary delays. Locks, an important component of waterway infrastructure, enable vessels to travel between waterways of varying depths and must be maintained consistently to avoid unexpected failures. However, with limited resources, it is difficult to preserve …

Harnessing Technology To Solve Social Problems, Ian Hassell

SMU Human Trafficking Data Conference

No abstract provided.

Evaluating Climate Sentiment In Sec 10-K Filings: S&P 50 Companies, Ruby Chu

Dissertations, Theses, and Capstone Projects

Evaluating Climate Sentiment in SEC 10-K Filings: S&P 50 Companies investigates how climate sentiment is portrayed in corporate financial reporting, focusing on SEC 10-K filings from leading S&P 50 companies. These filings offer detailed insights into financial performance, risks, and management discussions, providing a rich dataset for analyzing corporate behaviors with sustainability and environmental concerns. This study aims to shed light on the extent to which companies address environmental issues and the implications for environmental stewardship by analyzing how these topics are portrayed in their SEC 10-K filings. Drawing inspiration from established greenwashing indicator frameworks, the study develops a climate …

Enhancing Electrical Network Vulnerability Assessment With Machine Learning And Deep Learning Techniques, M Mishkatur Rahman, Ayman Sajjad Akash, Harun Pirim, Chau Le, Trung Le, Om Prakash Yadav

Northeast Journal of Complex Systems (NEJCS)

This research utilizes advanced machine learning techniques to evaluate node vul-
nerability in power grid networks. Utilizing the SciGRID and GridKit datasets, con-
sisting of 479, 16,167 nodes and 765, 20,539 edges respectively, the study employs
K-nearest neighbor and median imputation methods to address missing data. Cen-
trality metrics are integrated into a single comprehensive score for assessing node
criticality, categorizing nodes into four centrality levels informative of vulnerability.
This categorization informs the use of traditional machine learning (including XG-
Boost, SVM, Multilayer Perceptron) and Graph Neural Networks in the analysis.
The study not only benchmarks the capabilities of these …

Evaluating The Health Benefits And Cost-Effectiveness Of Dental Sealant Reapplication Among Children And Adolescents, Pritam Deb, Jayden Ayash, Christina Scherrer

Symposium of Student Scholars

Dental caries, commonly known as cavities, persist as a prevalent chronic disease among children. Dental sealants, which are transparent coatings applied to the molars, have been proven to prevent over 80% of caries in these teeth. However, the effectiveness of sealants diminishes over time, primarily due to their potential to detach shortly after application due to inadequate bonding, or else gradually over time. Notably, dental insurance coverage for resealing teeth after the initial sealant has been lost varies widely, with many policies only covering the cost of the initial application. This study employs a Markov model-based discrete event simulation to …

Effects Of Ti Addition On The Characteristics Of Al-10zn-6mg-2si/Zro2 Composites Produced By Squeeze Casting, Qesha Diva Prameshvara, Pipin Indah Lestari, Bondan Tiara Sofyan

Journal of Materials Exploration and Findings

Metal matrix composite (MMC) with 7xxx aluminum matrix is potential for ballistic applications due to the combination of strength, toughness, and light weight. Previous study successfully produced aluminum-based composites with SiC particles which were able to stop type III bullet, however cracks remained on back of the plate. Therefore, in this research, SiC was replaced by zirconia (ZrO₂) due to its high fracture toughness. Ti-B grain refiner was added to further improve toughness through grain boundary strengthening mechanism. This research developed 5 vol.% ZrO₂ strengthened Al-10Zn-6Mg-2Si composite with addition of Al-5Ti-1B grain refiner produced through squeeze casting …

Study On Human Integrity Management System Maturity Level For Supporting Asset Integrity And Process Safety Implementation, Anggiat M. Sihotang, Dedi Priadi, Datu Rizal Asral

Journal of Materials Exploration and Findings

The human factors (HF) are recognized as one of critical process safety barriers involved in normal and abnormal conditions in the oil and gas industry. In order to strengthen the HF roles as barriers we need to ensure that the actions generated are based on a valid risk assessment of the operation to be addressed by a relevant human factor analysis. Organizations within the oil and gas process have made much progress in understanding and implementing HF improvement programs. However, organizations are not always clear about what are their current situations in managing HF, their priorities for HF to be …

Analysis Of The Effect Of Different Surface Preparation Methods On Corrosion Resistance And Adhesion Strength Of Astm A36 Steel Substrate With Surface Tolerant Epoxy Paint As Coating Material, Irwan Wijaya Santoso, Daffa Aqila, Rini Riastuti, Rizal Tresna Ramadhani

Journal of Materials Exploration and Findings

In the industrial world, to extend the service life of materials, protection methods are carried out to slow down the material's corrosion rate. The protection method that is often used is the coating method. The coating method is a protection method by coating the substrate material using a coating material to prevent contact between the substrate material and the environment. In this research, the substrate material used is ASTM A36 steel and the coating material used is Surface Tolerant Epoxy paint. The independent variable used in this study lies in the surface preparation method which consists of: solvent cleaning, hand …

Model-Based Comparison Of Biological Organism And Electro-Mechanical System Resiliency Strategies, Nicholas Ratycz

Mechanical Engineering Undergraduate Honors Theses

Bio-inspired design has been used by many engineers to solve difficult problems or to make manufacturing processes more efficient. Biomimetics is the study of implementing the structure or function of biological substances, materials, mechanisms, and processes onto artificial ones that mimic the original. The goal of the BIASD tool is to provide bio-inspiration for engineers by studying the fault-adaptive strategies that biological systems use, rather than just their structure or function. In this thesis, the fault adaptive strategies of both a biological example and that of a real cubesat are compared using three types of model-based system diagrams to show …

Application Of Lean Six Sigma For Improving Quality Laboratory Process, Sarmad Al Hilli

Masters Theses & Specialist Projects

Oftentimes, manufacturing companies concentrate on improving the production processes and neglecting other processes like purchasing, IT, quality control, etc. Just like production processes, uncontrolled and non-optimized of any of these processes could be main reasons of product defects, late deliveries, and high costs. Recently, an automotive OEM (Original Equipment Manufacturer) in the southeastern United States faces difficulties in performing quality control operations in a way that matches the production pace. This inadequacy has increased due to changes in customer requirements and launches a new assembly line for a new customer. Therefore, the purpose of this study was to apply Lean …

Using Convolutional Neural Networks For Autonomous Drone Navigation, Joshua Jowers

Industrial Engineering Undergraduate Honors Theses

Unmanned Aerial Vehicles (UAVs), more commonly known as drones, serve various purposes, notably in military applications. Consequently, there arises a need for navigation methods impervious to intercepted signals [1]. Previous research has explored numerous solutions, including machine learning. This paper delves into a specific machine learning approach employing a Convolutional Neural Network (CNN) to discern image locations [2]. It elucidates the conversion of a CNN model between two machine learning libraries and presents results from multiple experiments examining parameters and factors influencing the approach's efficacy. These experiments encompass testing different data sources, image quantities, and processing pipelines to gauge their …

Great South Metals: Slitter Head Building Process, Nabhan Karim, Evan Swierski, Raven Morin, Patrick Kelsey, Michael Williams

Senior Design Project For Engineers

Great South Metals (GSM) operates two steel slitter machines, which take large coils of flat rolled steel and cut them into smaller strips for use in customers’ applications. Setting up the working components of each machine, called the slitter head, is a precise and arduous task. This system relies on several manually performed calculations and acute attention to detail; and thus, is prone to human error. The management at GSM commissioned our team to simplify the slitter head assembly process by creating an automated computer program and make additional recommendations to improve their operations.

The program we created is a …

Open-Source Optimization For Green Last Mile Delivery And Other Applications, John Sooter

Industrial Engineering Undergraduate Honors Theses

Solving combinatorial optimization problems at scale and of sufficiently interesting context has historically required commercial solvers and access to proprietary company data. The development of performant open-source mathematical programming software and crowdsourced datasets has created an opportunity for individuals and enterprises alike to consider alternative solutions to problems with social and personal implications. This honors thesis represents a summary of my undergraduate research work, an application of optimization to three distinct problems connected to these developments. First, we present an optimization study of a last mile delivery system that shows optimization for energy consumption can generate vehicleindependent fuel savings at …

Comparing North American Professional Sports League Season Formats Using Monte Carlo Simulation, Lathan Gregg

Industrial Engineering Undergraduate Honors Theses

Each NFL, NBA, and MLB season consists of a regular season, in which teams play a set number of scheduled games and a playoff, in which qualifying teams compete for a championship. At the conclusion of each season, teams are ranked based on their performance throughout the season. This study aims to investigate the ability of each league's season format to accurately rank teams using Monte Carlo simulation. Matches between two teams are simulated by using the team’s assigned strength ranks to calculate a winning probability for each team. The winning probabilities are simulated with different skill values, dictating how …

Sequential Optimization For Stressor-Informed Test Planning Through Integration Of Experimental And Simulated Data, Jacob Brecheisen

Data Science Undergraduate Honors Theses

This technical report details an innovative approach in reliability engineering aimed at maximizing system durability through a synergistic use of physical experimentation and computer-based modeling. Our methodology explores the efficient design and analysis of computer experiments and physical tests to facilitate accelerated reliability growth, while leveraging a sequential integration of data from these two distinct sources: costly physical experiments, characterized by random errors, and inexpensive computer simulations, marked by inherent systematic errors. The key innovation lies in the adoption of a closed-loop design and analysis method. This method begins by identifying a viable subset of important environmental stressors—such as temperature, …

Investigating Potential Improvements To Mbse Software To Support Dodaf, Jennifer Marie Kimpson

Theses and Dissertations

The integration of models created through model-based systems engineering methods with DoDAF is not a new concept. By creating DoDAF-aligned models, DoD program managers are following DoD guidelines to hopefully achieve more effective communication with stakeholders and improve efficiency of their programs. With the use of MBSE tools to create these models, DoD program managers are able to take further advantage of the benefits of MBSE methods. However, even with the use of MBSE tools, there continue to be issues throughout DoD programs. The literature has shown that a continuous improvement approach regarding the use of MBSE tools with DoDAF …

Cost-Risk Analysis Of The Ercot Region Using Modern Portfolio Theory, Megan Sickinger

Master's Theses

In this work, we study the use of modern portfolio theory in a cost-risk analysis of the Electric Reliability Council of Texas (ERCOT). Based upon the risk-return concepts of modern portfolio theory, we develop an n-asset minimization problem to create a risk-cost frontier of portfolios of technologies within the ERCOT electricity region. The levelized cost of electricity for each technology in the region is a step in evaluating the expected cost of the portfolio, and the historical data of cost factors estimate the variance of cost for each technology. In addition, there are several constraints in our minimization problem to …

An Adaptive Large Neighborhood Search For The Multi-Vehicle Profitable Tour Problem With Flexible Compartments And Mandatory Customers, Vincent F. Yu, Nabila Yuraisyah Salsabila, Aldy Gunawan, Anggun Nurfitriani Handoko

Research Collection School Of Computing and Information Systems

The home-refill delivery system is a business model that addresses the concerns of plastic waste and its impact on the environment. It allows customers to pick up their household goods at their doorsteps and refill them into their own containers. However, the difficulty in accessing customers’ locations and product consolidations are undeniable challenges. To overcome these issues, we introduce a new variant of the Profitable Tour Problem, named the multi-vehicle profitable tour problem with flexible compartments and mandatory customers (MVPTPFC-MC). The objective is to maximize the difference between the total collected profit and the traveling cost. We model the proposed …

Mathematical Modeling For Dental Decay Prevention In Children And Adolescents, Mahdiyeh Soltaninejad

Dissertations

The high prevalence of dental caries among children and adolescents, especially those from lower socio-economic backgrounds, is a significant nationwide health concern. Early prevention, such as dental sealants and fluoride varnish (FV), is essential, but access to this care remains limited and disparate. In this research, a national dataset is utilized to assess sealants' reach and effectiveness in preventing tooth decay, particularly focusing on 2nd molars that emerge during early adolescence, a current gap in the knowledge base. FV is recommended to be delivered during medical well-child visits to children who are not seeing a dentist. Challenges and facilitators in …

Analyzing The Impact Of Socioeconomic Factors On Cancer Clinical Trials Accessibility In The U.S. Using Machine Learning, Krysta L. Ray, Hiromi Honda

ATU Research Symposium

While cancer impacts all segments of the United States population, specific groups experience a disproportionate burden of the disease due to social, environmental, and economic disadvantages. This research examines the correlation between socioeconomic factors and the accessibility of cancer clinical trials across U.S. counties, employing a comprehensive dataset, County-Level Socioeconomic and Cancer Clinical Trial Data from Noah Ripper, and advanced machine-learning techniques. Our findings, derived from regression analysis and machine learning models like gradient boosting, highlight significant disparities in trial availability linked to socioeconomic indicators, including poverty rates, population estimates, median income, incidence rates, and mortality rates. Many regression models …